nairobi county smart survey report survey...vii with chills (35.4%) and watery diarrhea (23.1%)....
TRANSCRIPT
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NAIROBI COUNTY
SMART SURVEY REPORT
FEBRUARY 2020
Supported by
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TABLE OF CONTENTS
LIST OF FIGURES ............................................................................................................................................... iii LIST OF TABLES ................................................................................................................................................. iii ACRONYMS ........................................................................................................................................................ iv ACKNOWLEDGEMENTS ...................................................................................................................................... v EXECUTIVE SUMMARY ...................................................................................................................................... vi 1.0: INTRODUCTION ............................................................................................................................................ 1
1.1: Background Information .................................................................................................................................. 1 1.2: Rationale of Survey ........................................................................................................................................... 2
2.0: SURVEY METHODOLOGY ............................................................................................................................. 3 2.1 Study Population ................................................................................................................................................. 3 2.3: Survey Design ..................................................................................................................................................... 3 2.4: Anthropometric Sample Size .......................................................................................................................... 3 2.6: Survey Organisation.......................................................................................................................................... 4 2.7: Questionnaire ...................................................................................................................................................... 5 2.9: Data Analysis ...................................................................................................................................................... 5
3.0: SURVEY FINDINGS ....................................................................................................................................... 6 3.1: HOUSEHOLD DEMOGRAPHICS ..................................................................................................................... 6 3.1.1 Characteristics of Respondents ................................................................................................................... 6 3.1.2 Gender of the children in the survey........................................................................................................... 6 3.1.3 Caregivers’ level of education and school enrolment ............................................................................ 6 3.1.5: Marital Status ................................................................................................................................................... 7 3.1.5: Households’ head main source of income and livelihood .................................................................. 7 3.2 NUTRITION STATUS OF CHILDREN ............................................................................................................... 8 3.2.1 Prevalence of acute malnutrition based on weight-for-height z-score. ............................................. 8 3.2.2 Prevalence of Acute malnutrition by MUAC .............................................................................................. 9 3.2.3 Prevalence of underweight ..........................................................................................................................10 3.2.4 Prevalence of stunting. .................................................................................................................................10 3.2.5 Prevalence of Overweight. ...........................................................................................................................11 3.3 ACCESS AND UTILIZATION OF HEALTH AND NUTRITION SERVICES...............................................12 3.3.1 Vitamin A supplementation .........................................................................................................................12 3.3.2 Deworming .......................................................................................................................................................13 3.3.2 Child Immunizations ......................................................................................................................................13 3.3.3 Morbidity ..........................................................................................................................................................14 3.3.4 Health Seeking Behaviour ...........................................................................................................................15 3.4 WATER AND SANITATION ..............................................................................................................................15 3.4.1 Main source of water .....................................................................................................................................15 Figure 10: Main source of water ...........................................................................................................................16 3.4.2 Water Consumption .......................................................................................................................................16 3.4.3 Access of Water .............................................................................................................................................17 3.4.4 Access to Sanitation Facility .......................................................................................................................17 3.4.5 Water Treatment and Hand washing .........................................................................................................18 3.4.6 Payment and Water Storage ........................................................................................................................18 3.5: Ownership of mosquito net ...........................................................................................................................19 3.6 MATERNAL NUTRITION ...................................................................................................................................19 3.6.1: Maternal Nutrition Status ............................................................................................................................19 3.6.2 IFAS Supplementation ..................................................................................................................................19 3.7 FOOD SECURITY ...............................................................................................................................................20 3.7.1 Minimum Dietary Diversity (24-Hour Recall)-Women............................................................................20 3.7.2 Minimum Dietary Diversity for Women .....................................................................................................21 3.7.3 Household Dietary Diversity (24 hour Recall) .........................................................................................22 3.7.4 Average days food groups are consumed showing consumption of micronutrients ..................22 3.7.5 Food Consumption Score ............................................................................................................................23 3.8 Food Fortification ..............................................................................................................................................23
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3.9 Coping Strategy Index ......................................................................................................................................24 4.0: Conclusions................................................................................................................................................ 25 APPENDICIES.................................................................................................................................................... 27
Appendix 1: Plausibility Results ..........................................................................................................................27 Appendix 2: Calendar Of Local Events ..............................................................................................................28 Appendix 4: Questionnaires ..................................................................................................................................30
LIST OF FIGURES
Figure 1: Administrative map ......................................................................................................................................... 1 Figure 2: Admission trends of OTP anD sfp .................................................................................................................. 2 Figure 3: Highest level of education of the household head .......................................................................................... 7 Figure 4: Marital status ................................................................................................................................................. 7 Figure 5: vitamin A supplementation (6-59 months) .................................................................................................... 13 Figure 6: MEASLES, OPV1 and opv3 coverage .......................................................................................................... 14 Figure 7: Child morbidity ............................................................................................................................................. 14 Figure 8: Health seeking behaviour ............................................................................................................................. 15 Figure 9: Main water sources ...................................................................................................................................... 16 Figure 10: Main source of water ..................................................................................................................................... 16 Figure 11: sanitation facility ........................................................................................................................................ 17 Figure 12: mosquito net ownership .............................................................................................................................. 19 Figure 13: ifas supplementation ................................................................................................................................... 20 Figure 14: Women dietary diversity ............................................................................................................................. 21 Figure 15: MDD-w ....................................................................................................................................................... 21 Figure 16: Household dietary diversity ........................................................................................................................ 22 Figure 17: average number of days of consumption of micronutrient rich foods ........................................................ 23 Figure 18: food consumption score .............................................................................................................................. 23 Figure 19: Fortification and main maize flour consumed ............................................................................................ 24
LIST OF TABLES
Table 1: Summary Findings.......................................................................................................................................... vii Table 2: Sample size parameters .................................................................................................................................... 4 Table 3: cluster distribution ........................................................................................................................................... 4 Table 4: Response rate ................................................................................................................................................... 6 Table 5: reason for being not in school .......................................................................................................................... 7 Table 6: households' head main source of income and occupation ................................................................................ 8 Table 7: prevalence of acute malnutrition based on weight for height z-score(and/or Oedema)and by sex .................. 9 Table 8: prevalence of acute malnutrition based on muac ............................................................................................. 9 Table 9: prevalence of underweigght based on weight for age .................................................................................... 10 Table 10: prevalence of stunting based on height for age ............................................................................................ 11 Table 11: prevalence of overweight.............................................................................................................................. 12 Table 12:Water consumption ........................................................................................................................................ 16 Table 13: trekking and queueing for water................................................................................................................... 17 Table 14: Handwashing at critical times and water treatment..................................................................................... 18 Table 15: water storage and payment .......................................................................................................................... 18 Table 16: Maternal nutrition muac .............................................................................................................................. 19 Table 17: coping strategy index ................................................................................................................................... 24 Table 18: recommendations ......................................................................................................................................... 25
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ACRONYMS
AMTSL: Active Management of Third Stage of Labor ANC: Antenatal Care APHRC: African Population Health Research Centre BCG: Bacillus Calmette – Guerin BFCI Baby Friendly Community Initiatives CHW Community Health Workers CHEW Community Health Extension Workers C.I.: Confidence Interval DMOH: District Ministry of Health DNO: District Nutrition Officer DPT: Diphtheria, Pertussis and Tetanus EBF: Exclusive Breastfeeding Rate ENA: Emergency Nutrition Assessment FTC: Feed the Children GAM: Global Acute Malnutrition HiNi: High Impact Nutrition Intervention IMR: Infant Mortality Rate IYCN: Infant and Young Children Nutrition KPC: Knowledge, Practice and Coverage MAM: Moderate Acute Malnutrition MIYCN: Maternal Infant and Young Children Nutrition MNCH: Maternal and New-Born Child Health MoH: Ministry of Health MoH: Ministry of Health MUAC: Mid-Upper Arm Circumference SAM: Severe Acute Malnutrition SMART: Standardized Measurement of Relief and Transition SPSS: Statistical Package for Social Sciences TBA: Traditional Birth Attendants UNICEF: United Nations Children Fund VAD: Vitamin A Deficiency WFA: Weight for Age WFH: Weight for Height WHO: World Health Organization
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ACKNOWLEDGEMENTS
We sincerely acknowledge the participation of our partners at different levels of the survey exercise. In particular, we acknowledge UNICEF for funding the Survey, Concern Worldwide, USAID Aphia Jijini and the Ministry of Health for their direct participation in the whole exercise. Special attributes goes to the Nairobi County Health Department and the National Nutrition Information Working Group for validating the methodology and the results. At the community level, special gratitude is owed to all the households who made the exercise a reality. The Community Health Assistants and the Community Health Volunteers through the Community Strategy focal persons are also acknowledged for their role in mobilizing the community and acting as guides to the enumerators during the exercise. The survey teams composed of the enumerators and team leaders are highly appreciated for the hard work of collecting the high quality data to the best of their abilities. Lastly, we appreciate the active role played by the County Health Management Team and Sub County Nutrition Officers from all the 10 Sub-Counties within Nairobi City.
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EXECUTIVE SUMMARY
Nairobi County borders Kiambu County to the North and West, Kajiado to the South and Machakos to the East. The County has experienced very rapid population growth over the last 30-40 years. According to the 2019 Kenya National Population and Housing Census, the County has population estimate of 4.39 million. Significantly, 60% of this population live in the informal settlements covering about only 5% of the land (UN Habitat and the Kenya Slum Upgrading Programme). In addition, the County has the largest informal settlements in East and Central Africa namely; Kibra, Kawangware, Mathare, Kangemi, Korogocho, Majengo, Mukuru and Kiambiu with limited access to appropriate housing, electricity and sanitation. The precarious physical, social and economic conditions of these settlements heavily affect residents’ health and environment in addition to severely constraining the local economic development.1 This survey was proposed after February 2019 Kenya Food Security Steering Group report where the County was rated third highest in estimated Caseloads for Children 6-59months that require treatment for acute malnutrition. Persistent drought and food prices inflation during the past years led to increased food insecurity and likelihood of increased malnutrition rate. Therefore, the information collected will support the Nairobi County government in decision making and nutrition programming. The overall objective of the survey is to determine the nutrition status of children aged 6- 59 months old and
Women of reproductive age 15-49 Years in the informal settlements within Nairobi County. Specific objectives
of the survey were : To estimate the current prevalence of acute malnutrition in children aged 6 – 59 months,
to estimate the nutritional status of women of reproductive age 15-49 years using MUAC measurements, to
estimate Measles, de-worming, BCG vaccination and ‘Vitamin A’ supplementation coverage for children 9-59
months and 6-59 months respectively, to establish the Morbidity rates of children 6-59 months 2 weeks prior
to the survey and to collect information on household food security, water, sanitation, and hygiene practices.
The target geographical area was the informal settlement covering ten sub counties including Ruaraka, Makadara, Lang’ata, Dagoretti, Kamukunji, Starehe, Kasarani, Embakasi East, Embakasi West and Westlands. Due to the complex nature of the urban population, the survey adopted a 3 stage sampling technique where mapping of all the informal settlements was done before the survey. The First stage sampling involved the selection of blocks using Simple Random Sampling (SRS) where all the target informal settlements were divided into blocks of approximately 1000 HHs per block. The second stage sampling involved selection of segments which was considered to be the clusters using SRS. The sampled blocks were further divided into 10 segments of approximately 100 HHs per segment. Lastly, the third stage was led by the village guide and a systematic sampling method was used in household selection whereby survey teams developed a sampling frame in each of the village sampled during the second stage sampling covering 16 households per cluster. The survey team were trained for 4 days including pretesting of the survey tools thereafter they proceeded for
a 7 day data collection. Subsequently, daily data entry and analysis was done using ENA for SMART (July,
2015 Version). Further analysis was also done with Ms. Excel and SPSS version 20. Daily quality of data was
monitored through running the plausibility results for the anthropometric data and results feedback was
provided to the team on every morning before leaving for the field.
The survey findings indicated a global acute malnutrition (GAM) prevalence rate of 3.9 % (2.7 - 5.6 95% C.I.) while the prevalence for severe malnutrition was at 0.0 % (0.0 - 0.0 95% C.I.). This is generally classified as low by the WHO classification of malnutrition. However, going by the number of acute malnutrition caseloads, there is need of urgent concern and concentered efforts to tackle malnutrition. In addition, the prevalence of underweight is at 9.6 % (7.6 - 12.0 95% C.I.) with 2.5 % (1.5 - 4.1 95% C.I.) severely underweight. Significantly, the stunting prevalence is high at 24.0 % (20.9 - 27.5 95% C.I.) with 4.4 % (3.1 - 6.2 95% C.I.) of the children severely stunted. About 26.8% (212) of children aged 6-59 months reported to have been ill two weeks prior to survey. The most prevalent illness during this period was acute respiratory illnesses/ cough at 65.1%, fever
1 Nairobi County Development Plan 2018
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with chills (35.4%) and watery diarrhea (23.1%). However, only 72.2% (153) of children visited health facility during with illness two weeks prior to the survey with majority attending public clinics (51.0%).
Only 46.4% of children aged 12-59 Months received twice yearly Vitamin A supplementation while 60.3% received zinc supplement and oral rehydration salts (ORS) during episode of diarrhea. Additionally, 89.1% (n=659) of children were reported to have received BCG vaccine. With regards to water, sanitation and hygiene 47.0% (n=469) of the households reported treating water before drinking with only 12.5% (n=125) practicing proper hand washing at the 4 critical times. The Women dietary diversity was optimal with 60 % receiving more than five food groups. However, iron folic supplementation coverage for more than 90 days was low at 53.8%. The following table presents the summary of the indicators TABLE 1: SUMMARY FINDINGS
February 2020
All (n = 717) Boys (n = 360) Girls (n = 357)
Prevalence of global malnutrition (<-2 z-score and/or Oedema)
(28) 3.9 % (2.7 - 5.6 95% C.I.)
14) 3.9 % (2.4 - 6.3 95% C.I.)
(14) 3.9 % (2.2 - 6.8 95% C.I.)
Caseload 23,438
Prevalence of severe malnutrition (<-3 z-score and/or Oedema)
(0) 0.0 % (0.0 - 0.0 95% C.I.)
(0) 0.0 % (0.0 - 0.0 95% C.I.)
(0) 0.0 % (0.0 - 0.0 95% C.I.)
Caseload 0
Prevalence of global malnutrition by MUAC (< 125 mm and/or Oedema)
(20) 2.7 % (1.8 - 4.1 95% C.I.)
(11) 3.0 % (1.8 - 5.1 95% C.I.)
(9) 2.5 % (1.3 - 4.6 95% C.I.)
Prevalence of severe malnutrition by MUAC (< 115 mm and/or Oedema)
(1) 0.1 % (0.0 - 1.0 95% C.I.)
(0) 0.0 % (0.0 - 0.0 95% C.I.)
(1) 0.3 % (0.0 - 2.0 95% C.I.)
Prevalence of underweight (<-2 z-score)
(69) 9.6 % (7.6 - 12.0 95% C.I.)
(38) 10.5 % (7.5 - 14.6 95% C.I.)
(31) 8.6 % (6.0 - 12.2 95% C.I.)
Prevalence of severe Underweight (<-3 z-score)
(18) 2.5 % (1.5 - 4.1 95% C.I.)
(10) 2.8 % (1.3 - 5.6 95% C.I.)
(8) 2.2 % (1.1 - 4.5 95% C.I.)
Prevalence of Stunting (<-2 z-score)
(170) 24.0 % (20.9 - 27.5 95% C.I.)
(99) 28.3 % (23.7 - 33.4 95% C.I.)
(71) 19.9 % (16.0 - 24.4 95%
C.I.)
Prevalence of severe stunting (<-3 z-score)
(31) 4.4 % (3.1 - 6.2 95% C.I.)
(22) 6.3 % (4.3 - 9.2 95% C.I.)
(9) 2.5 % (1.3 - 5.0 95% C.I.)
Category Indicator
Nairobi County
n N %
Immunization /Vaccination and supplementation
Deworming (12-59 Months) 430 619 69.5%
Measles at 9 Months (Yes by Card) 306 675 60.3%
Measles at 9 Months (Yes by Recall) 350 507 36.7%
Measles at 18 Months (Yes by Card) 189 740 47.9%
Measles at 18 Months (Yes by Recall) 239 740 35.9%
BCG by Scar 659 740 94.2%
OPV 1 (Yes by Card) 372 740 63.0%
OPV 1 (Yes by Recall) 740 740 36.3%
OPV 3 (Yes by Card) 363 740 60.8%
OPV 3 (Yes by Recall) 353 740 35.7%
Supplementation Zinc Supplementation 35 58 60.3%
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Vitamin A Supplementation (12-59 Months) - Once 498 731 80.2%
Vitamin A Supplementation (6-11 Months )- Once 101 117 83.5%
Vitamin A Supplementation (6-11 Months )- Once verified by card 75 121 62.0%
Vitamin A Supplementation (12-59 Months) - Twice 287 619 46.4%
Vitamin A Supplementation (6-59 Months) - Once 599 740 80.9%
Morbidity
Prevalence of Fever 75 212 35.4%
Prevalence of ARI 138 212 65.1%
Prevalence of Watery Diarrhea 49 212 23.1%
Prevalence of Bloody Diarrhea 0 212 0 %
Health Seeking behavior Health Seeking Behavior 153 212 72.2%
Hygiene
Household Which wash Hands 860 89.9%
After Toilet 805 93.6%
Before cooking 416 49.5%
Before Eating 714 83.0%
After taking children to the toilet 286 33.3%
Hand washing by Soap and water 741 86.2%
hand washing 4 critical times 161 18.7%
Total weighted Coping Strategy Score 13.07
The acute malnutrition situation in the Nairobi informal settlements is low according to the World Health Organization classification. However, in terms of caseloads due to high population density in the Nairobi County, the number remains considerably high. Despite reduction in the stunting and underweight level, the rate still remains high at 24% and 9.6% respectively. However, there was notable difference in underweight distribution among boys and girls with underweight rates at 10.5% and 8.6% respectively. In terms of morbidity as a major contributor to malnutrition, the situation improved significantly compared to the previous year. The proportion of children reported ill 2 weeks before the study significantly dropped from 46.1% in 2017 to 38.9% in 2020 indicating a relatively more healthy population. Among the children reported ill, the major ailments included ARIs at 53.5%, Fever at 29.5% and watery diarrhea at 20.1%.Significantly, poor water and sanitation hygiene conditions in informal settlements were major contributor to childhood illnesses such as diarrhea. Only 12.5% of the population practice hand washing at 4 critical times. This depict a deterioration in appropriate hygiene practices hence contributing highly to high malnutrition rates in the county.As a recommendation, there is need to adopt the recently developed County nutrition action plan (2018-2022).In addition, the County should procure IFAS to increase the supplementation coverage
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1.0: INTRODUCTION
1.1: Background Information
According to the Kenya National Bureau of Statistics (KNBS) population census projection 2018, Nairobi
County has a population estimate of 4,397,073. It borders Kiambu to the North, Kajiado to the South and
Machakos to the East with a total area of 696.1 Km2.It is located between longitudes 360 45’ East, latitudes
10 18’ South and an altitude of 1,798 meters above the sea level. This population is distributed in 17
administrative Sub Counties which have been merged to 10 health administrative units. Moreover, about
60% of the Nairobi population is estimated to be living in the informal settlements, covering only 5% of the
Nairobi land.
FIGURE 1: ADMINISTRATIVE MAP
The County typifies the rapid urbanization and population explosion in Sub-Saharan Africa. As the capital
and largest city of Kenya, Nairobi has always been the major attraction of various segments of the Kenyan
population, from both rural and other urban areas in search of better livelihood opportunities. The
consequences of the rapid and uncontrolled population explosion is the proliferation of the informal
settlements. Therefore, meeting the increasing demand of this new population for basic services is a daunting
challenge for policy makers and specifically, for the Nairobi County Government.
These informal settlements are complex: economic, social and governing structures are more complicated
than rural localities. They also contain fragmented and less cohesive communities.2. Informal settlement
conditions create greater exposure to violence (often sexual and gender based), unwanted pregnancy and
adverse health and nutrition outcomes, particularly for women and their children.
2 Zulu, E.M., Beguy, D., Ezeh, A.C., Bocquier, P., Madise, N.J., Cleland, J. and J. Falkingham, 2011, Urbanisation, Poverty, and Health Dynamics in sub-Saharan Africa: Insights from Nairobi Slum Settlements, Journal of Urban Health, Bulletin of the New York Academy of Medicine, Vol 88, Supplement 2.
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The livelihood of most informal settlement inhabitants’ income comes from informal economic activities and
formal wage employment. This has been decreasing, as the public sector continues to retrench its
employees. With adverse poverty and under employment the populations are highly vulnerable to shocks
from price increase, disease outbreaks and political unrest. This results into a high disease burden, food
insecurity and ultimately high levels of malnutrition and mortality.3
1.2: Rationale of Survey The survey was proposed after February 2019 Kenya Food Security Steering Group (KFSSG) report where the Nairobi County was rated third highest among the 47 Counties with the estimated caseloads for Children 6-59 months that require treatment for acute malnutrition. Significantly, over the last year’s inflation rates have increased among the urban dwellers with most affected populations are people living in the informal settlement. Therefore, the survey determined the extent of the effects of inflation. In the year 2019 most parts of the Country experienced drought. Consequently, this had effects on food production and as a result many household in both rural and urban areas experienced food insecurity. Additionally, looking at the admission trends for both Supplementary Feeding Program and Out Patient Therapeutic Program from March 2019 to February 2020 there are fluctuations across the months. As a result, this survey was designed to give a clear picture of the nutrition situation in the County. More importantly, the information collected will support the Nairobi County government for decision making and nutrition programming.
FIGURE 2: ADMISSION TRENDS OF OTP AND SFP
1.3 Survey Objectives
▪ The overall objective of the survey is to determine the nutrition status of children aged 6- 59 months
and Women of reproductive age 15-49 Years in the urban informal settlement of Nairobi County.
1.4: Specific objectives of the Survey:
• To assess current prevalence of acute malnutrition in children aged 6-59 months.
• To compare the Overall nutrition changes with the previous GAM and SAM.
• To determine the nutritional status of women of reproductive age (15-49 years)
• To determine immunization coverage for OPV1 & 3 for children aged 6-59 months.
• To determine Vitamin A supplementation Coverage for children aged 6-59 Months.
3 Concern Worldwide Situation Analysis 2017.
517581
648553
466 424480 510
389 391
534444
1,229
1,4871,403
1,234
1,059988
1,410
1,159
870
675
919865
0
200
400
600
800
1000
1200
1400
1600
Mar-19 Apr-19 May-19 Jun-19 Jul-19 Aug-19 Sep-19 Oct-19 Nov-19 Dec-19 Jan-20 Feb-20
OTP SFP
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• To determine deworming coverage for children aged 12 - 59 months.
• To determine Measles Coverage for the children aged 9-59 Months.
• To determine the prevalence of common illnesses (diarrhea, Fever and ARI).
• To establish the coverage of iron/folic acid supplementation and consumption during pregnancy among lactating women
• To collect information on possible underlying causes of malnutrition such as household food security, water, sanitation, and hygiene practices
2.0: SURVEY METHODOLOGY
2.1 Study Population
The target population were children aged 6 – 59 months and the women of reproductive age 15-49 years.
The survey subject included the target population in the Nairobi Urban informal settlements. It was estimated
that the County had 4.39 Million people based on the Census 2019.The same projections for children aged
0 -59 months indicated an estimated population of 219,500. All the villages (clusters/sampling units) in
Nairobi County which were accessible, secure or not deserted were included in the primary sampling frame.
2.2: SURVEY AREA
The target geographical area was the informal settlements in the Nairobi County. Specifically, the survey
covered the following 10 sub counties; Ruaraka, Makadara, Lang’ata, Dagoretti, Kamukunji, Starehe,
Kasarani, Embakasi East and Embakasi West and Westlands.
2.3: Survey Design
The survey adopted a three stage cluster sampling.
The First stage sampling:
This involves selection of blocks using Simple Random Sampling (SRS). All the target informal settlements
were divided into block of approximately 1000 HHs per block.
The second stage sampling:
This involves selection of segments which was considered to be the clusters using SRS. The sampled blocks were further divided into 10 segments of approximately 100 HHs per segment. The Third stage: Led by the village guide, systematic sampling method was used in household selection. The survey teams developed a sampling frame in each of the village sampled during the 2st stage sampling. All the households were listed. From the list the survey teams systematically selected 16 households where they administered household questionnaire (in all households). In addition, anthropometric, morbidity and immunization questionnaire was administered in the households with children aged 6 to 59 months.
2.4: Anthropometric Sample Size
The anthropometric survey sample size was calculated using the SMART survey calculator. The parameters
of interest were captured in the ENA July 2015 software and the respective number of children required for
the survey computed as indicated below.
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2.5 Sample Size Calculation TABLE 2: SAMPLE SIZE PARAMETERS
Parameter Value Source/Rationale
Estimated Prevalence (Wasting) 4.6% 2017 Nairobi slums Nutrition Survey(Concern)
Precision 2.9 From SMART Global project
Design Effect 1.5 To cater for heterogeneity that may arise
Children to be included in Sample 327
Average Household Size 2.9 2019 KNBS
Population of Under-5 12.7% DHIS
Non-Response Rate 5% To cater for the non-response
Households to be included 1039
The targeted number of children for this survey was 327 children, during the survey 729 children were reached. In the sampled households, anthropometric measurements for children aged between 6 and 59 months were taken. In total, 64 sample clusters were covered and 16 households were systematically sampled in each cluster. Please find below cluster distribution table
TABLE 3: CLUSTER DISTRIBUTION
Informal Settlement Sub County
Sub County Population
Estimated Slum Population
Proportion Population
Cluster Distribution
Korogocho Ruaraka 780656 468394 18.65% 12
Viwandani/ Kaloleni Makadara 189536 113722 4.53% 3
Kibera Lang'ata 383266 229960 9.15% 6
Kawangware/Gatina Dagoretti 434208 260525 10.37% 7
Majengo/Kiambiu Kamukunji 268276 160966 6.41% 4
Mathare Starehe 206564 123938 4.93% 3
Gitare Marigu/Njiru Kasarani 626482 375889 14.96% 10
Mukuru/Kayole Soweto
Embakasi 988808 593285 23.62% 15
Githogoro Westland 308854 185312 7.38% 5
Total 4,186,650 2,511,991 100% 65
2.6: Survey Organisation
Coordination/Collaboration: Before the survey exercise was conducted, meetings were held with the key
stakeholders where they were briefed about the purpose, objectives and survey methodology. This included
validation of the methodology at the National Nutrition Information Technical Working Group (NITWG).
Selection of the Survey Team: To collect reliable and quality data, a clearly criteria for enumerators
selection was developed. Enumerators were finally selected based on past experience, ICT knowledge and
availability during training to the entire data collection period. This was done on competitive basis.
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Training of the Survey Team: The data collection teams were given 4-days training prior to field work. This
included tests to ensure standardization of measurement and recording practice. All data collectors were
trained on taking anthropometric measurements, completion of questionnaires and sampling methodology.
The data collection forms and questionnaires were pilot tested in clusters not selected to be part of the larger
SMART survey. This was done to ensure that the interviewers and respondents understood the questions
and hence follow the correct protocols. In addition, the teams were also trained on the digital data collection
methods.
Team work in the field: Ten Teams each with three members who had experience in data collection were
paired with each team consisting of 1 Team Leader and 2 Measurers. In addition, 10 Sub County supervisors
and County team leaders with extensive knowledge and experience on the surveys formed part of the team
to oversee the execution of the survey at the field level. The Survey Supervisors were the SCNOs; there
were also two overall Survey Coordinators, Nutrition officer from UNICEF and five staff from Concern
Worldwide. Finally, the movement from one sampled household to another in every enumeration areas was
facilitated by the Community Health Volunteers (CHVs) who were seconded by the Sub County Community
Strategy Focal persons and the CHAs.
Quality Assurance: Quality assurance was integrated in all phases of the survey process. Comprehensive
guidelines were developed and shared with the survey team members. The team leaders provided adequate
support, real-time response to emerging issues and feedback during data collection period. In addition,
enumerators reporting schedules and control forms were used to facilitate monitoring of activities. Field
monitoring teams provided technical, logistic and administrative aspects of enumeration in each cluster.
Selection of children for anthropometry: All children between 6-59 months of age staying in the selected household were included in the sample. The respondent was the primary caregiver of the index child/children. If a child and/or the caregiver were temporarily absent, then the survey team re-visited the household to collect the data at an appropriate time.
Selection of women for determination of nutritional status: The mother of the index child within the
reproductive age (15-49years) in the identified households and any other household member within the age
bracket was enlisted in the study and their MUAC measurements taken.
2.7: Questionnaire
The survey adopted the data collection tools validated by the Nutrition Information Working Group.
2. 8: Data collection. The data collection took 7 days. Sub County Nutrition Officers with support from implementing partner’s staff supervised the teams throughout the data collection period. Teams administered the standardized questionnaire to the mother or primary caregiver. Each survey team explained the purpose of the survey exercise, issues of confidentiality and thereafter obtained verbal consent before proceeding with the interview. The teams used ODK questionnaire in tablets to record the responses. In addition, the data was uploaded to KOBO Humanitarian servers at the end of each day. Subsequently, the anthropometric data was downloaded daily, reviewed/analyzed for plausibility and feedback provided to the teams, using daily customized scorecards
2.9: Data Analysis
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The data entry and analysis was done using ENA for SMART (July, 2015 Version). Further analysis was
done with Ms. Excel and SPSS version 20. Daily quality of data was monitored through running the plausibility
results for the anthropometric data and results were feedback to the team on every morning before leaving
for the field.
3.0: SURVEY FINDINGS
Section three presents the results and findings from the survey.
3.1: HOUSEHOLD DEMOGRAPHICS
3.1.1 Characteristics of Respondents
We had targeted 1039 households living in the informal settlements with children aged between 6 and 59 months inclusive of a 5% non-response rate. However, only 997 households were interviewed, contributing to a response rate of 96%. Insecurity was a major challenge faced by the team during data collection forcing some team to move out of their respective clusters before achieving the daily targets. TABLE 4: RESPONSE RATE
Household Number of Households
Targeted household 1039
Sampled household 997
Response rate 96%
3.1.2 Gender of the children in the survey
In overall, anthropometric measurements of 729 children aged 6-59 months were taken, with 527 being
children aged between 6-23 months and 202 being children aged 24-59 months. The sex ratio of male to
female was 0.85.This is within the recommended range of 0.8 to 1.2 and hence the sample was unbiased for
gender.
3.1.3 Caregivers’ level of education and school enrolment
Maternal education is a strong predictor of child stunting. Very often, a caregiver’s knowledge, attitude and
actions towards proper child caring practices are very important for development of a child. Poor child caring
practices increases morbidity and malnutrition levels. It is worth noting that Nairobi County has high literacy
levels. As shown in the graph below, 39.3% of caregivers were primary school education holders while 42%
were secondary school education holders with only 1.4 % of the caregivers having no formal education and
5.6% having pre-primary education.
7
FIGURE 3: HIGHEST LEVEL OF EDUCATION OF THE HOUSEHOLD HEAD
3.1.4: Reasons for non-school enrollment The main reasons why some of the children were not in school were as follows: 66.7% had not attained the age, 17% due to lack of school fees and other school related cost with 4.3% reported to be providing labor to the family. TABLE 5: REASON FOR BEING NOT IN SCHOOL
Reason For being not in School n % Chronic Sickness 2 1.7% Family Labor responsibilities 5 4.3% Fees or Cost 20 17.1% No school nearby 6 5.1% Migrated/moved from schools area 4 3.4% Teacher Absenteeism 2 1.7% Others i.e. Young to go to School 78 66.7%
3.1.5: Marital Status
Majority of the respondents (78.9%) were married, 1.4% were widowed while 15.4% were single with only
0.6% divorced.
FIGURE 4: MARITAL STATUS
3.1.5: Households’ head main source of income and livelihood
The main source of income and livelihood for the household heads in the urban informal settlement was
casual labor (61.4%), followed by employment at 15.7% and petty trade at 10.0%.
5.6%
39.3%42.0%
9.9%
1.4% 1.7%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
45.0%
Pre primary Primary Secondary Tertiary None Others
78.9%
15.4%
1.4% 0.6% 3.6%
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
Married Single Widow Divorced Separated
8
TABLE 6: HOUSEHOLDS' HEAD MAIN SOURCE OF INCOME AND OCCUPATION
Indicators Occupation n %
Main Occupation
Livestock Herding 1 0.1%
Own Farm labor 4 0.4%
Employed 157 15.7%
Waged (Casual labor) 612 61.4%
Petty trade 100 10.0%
Merchant/Trader 50 5.0%
Firewood/Charcoal 2 0.2%
Others 71 7.1%
Main source of income
Sale of livestock 1 0.1%
Sale of livestock products 2 0.2%
Sale of crops 8 0.8%
Petty trading 109 10.9%
Casual labor 621 62.3%
Permanent Job 140 14.0%
Sale of Personnel assets 14 1.4%
Remittance 2 0.2%
Income earned by Children 2 0.2%
Others 98 9.8%
3.2 NUTRITION STATUS OF CHILDREN
The Global Acute Malnutrition (GAM) is the index which is used to measure the level of wasting in any given population. It is the proportion of children with a z-score of less than -2 weight-for-height and/or presence of bilateral edema. Severe Acute Malnutrition (SAM) was defined as the proportion of children with a z-score of less than -3 and/or presence of Oedema. Further, using the mid-upper arm circumference (MUAC), GAM was defined as the proportion of children with a MUAC of less than 125 mm and/or presence of Oedema while SAM was defined as the proportion of children with a MUAC of less than 115 mm and/or presence of edema.
Malnutrition by Z-Score: WHO (2006) Standard (summary)
• Severe acute malnutrition is defined by WFH < -3 SD and/or existing bilateral Oedema on the lower limbs
• Moderate acute malnutrition is defined by WFH < -2 SD and >-3 SD and no Oedema
• Global acute malnutrition is defined by WFH < -2 SD and/or existing bilateral Oedema
Malnutrition by MUAC (Summary)
• Severe malnutrition is defined by MUAC<115 mm and/or presence of bilateral Oedema
• Moderate malnutrition is defined by MUAC < 125 mm and ≥115 mm and no Oedema
• Global acute malnutrition is defined by MUAC <125 mm and/or existing bilateral Oedema 3.2.1 Prevalence of acute malnutrition based on weight-for-height z-score. The overall GAM Rate for children aged 6-59 months was low at 3.9 % (2.7 - 5.6 95% C.I). Additionally, the prevalence of SAM among the same age bracket was very low at 0.0% based on the WFH and/or edema. Moreover, there was no GAM prevalence variance in gender between girls and boys affected.
9
When compared with the SMART survey conducted in 2017(GAM 4.6%), the results shows that the GAM
Rate from this survey is relatively lower, although no statistically significant difference. SHowever, there is
need for concerted efforts by all stakeholders to address the major drivers of malnutrition in the informal
settlements.
TABLE 7: PREVALENCE OF ACUTE MALNUTRITION BASED ON WEIGHT FOR HEIGHT Z -SCORE(AND/OR OEDEMA)AND BY SEX
All
n = 717
Boys
n = 360
Girls
n = 357
Prevalence of global malnutrition
(<-2 z-score and/or Oedema)
(28) 3.9 %
(2.7 - 5.6 95% C.I.)
(14) 3.9 %
(2.4 - 6.3 95% C.I.)
(14) 3.9 %
(2.2 - 6.8 95% C.I.)
Prevalence of moderate malnutrition (<-2 z-score and >=-3 z-score, no Oedema)
(28) 3.9 %
(2.7 - 5.6 95% C.I.)
(14) 3.9 %
(2.4 - 6.3 95% C.I.)
(14) 3.9 %
(2.2 - 6.8 95% C.I.)
Prevalence of severe malnutrition
(<-3 z-score and/or Oedema)
(0) 0.0 %
(0.0 - 0.0 95% C.I.)
(0) 0.0 %
(0.0 - 0.0 95% C.I.)
(0) 0.0 %
(0.0 - 0.0 95% C.I.)
3.2.2 Prevalence of Acute malnutrition by MUAC Malnutrition can also be diagnosed using MUAC which is also a very good predictor of the risk of death. Analysis of the nutrition status for children aged 6 to 59 months based on MUAC and /or presence of Oedema resulted to GAM of 2.7 %(1.8 - 4.1 95% C.I) and SAM of 0.1 % (0.0 - 1.0 95% CI)
TABLE 8: PREVALENCE OF ACUTE MALNUTRITION BASED ON MUAC
All
n = 729
Boys
n = 367
Girls
n = 362
Prevalence of global malnutrition
(< 125 mm and/or Oedema)
(20) 2.7 %
(1.8 - 4.1 95% C.I.)
(11) 3.0 %
(1.8 - 5.1 95%
C.I.)
(9) 2.5 %
(1.3 - 4.6 95%
C.I.)
Prevalence of moderate malnutrition
(< 125 mm and >= 115 mm, no Oedema)
(19) 2.6 %
(1.7 - 3.9 95% C.I.)
(11) 3.0 %
(1.8 - 5.1 95%
C.I.)
(8) 2.2 %
(1.1 - 4.3 95%
C.I.)
Prevalence of severe malnutrition
(< 115 mm and/or Oedema)
(1) 0.1 %
(0.0 - 1.0 95% C.I.)
(0) 0.0 % (1) 0.3 %
10
(0.0 - 0.0 95%
C.I.)
(0.0 - 2.0 95%
C.I.)
In comparison with the previous SMART survey results in 2017, the GAM by MUAC was 2.6% (1.5- 4.3 95%) therefore, there was no significant difference.
3.2.3 Prevalence of underweight Percentage of children underweight describes how many children under five years have a weight for-age below -2 Z score standard deviations of the WHO reference median. In addition, children whose weight for age falls below -3 standard deviation of the WHO reference population were classified as severe underweight. The measure of underweight gives a mixed reflection of both the current and past nutrition experience by a population and is very useful in growth monitoring. According to Nairobi Cross Sectional survey conducted in 2012, children born in the informal settlements had lower birth weights relative to their counterparts at the national level and in Nairobi as a whole. This has been associated with preterm delivery or restricted fetal growth resulting largely from poor maternal health and nutrition. TABLE 9: PREVALENCE OF UNDERWEIGGHT BASED ON WEIGHT FOR AGE
All
n = 720
Boys
n = 361
Girls
n = 359
Prevalence of underweight
(<-2 z-score)
(69) 9.6 %
(7.6 - 12.0 95% C.I.)
(38) 10.5 %
(7.5 - 14.6 95%
C.I.)
(31) 8.6 %
(6.0 - 12.2 95%
C.I.)
Prevalence of moderate
underweight
(<-2 z-score and >=-3 z-score)
(51) 7.1 %
(5.4 - 9.3 95% C.I.)
(28) 7.8 %
(5.2 - 11.3 95%
C.I.)
(23) 6.4 %
(4.1 - 10.0 95%
C.I.)
Prevalence of severe underweight
(<-3 z-score)
(18) 2.5 %
(1.5 - 4.1 95% C.I.)
(10) 2.8 %
(1.3 - 5.6 95%
C.I.)
(8) 2.2 %
(1.1 - 4.5 95%
C.I.)
The results in the above table shows that the prevalence of underweight using the weight-for-age z-score was 9.6% (7.6 - 12.0 95% C.I.).This prevalence of underweight was classified as medium using the WHO classification of underweight4. On the other hand, the overall prevalence of severe underweight was found to be 2.5 % (5.4 - 9.3 95% C.I.) which is considered normal. When compared with the SMART survey conducted in 2017 where underweight was 11.4 % (8.8 - 14.7 95% C.I.) , there was a reduction in underweight rate but with no insignificant difference. 3.2.4 Prevalence of stunting.
The prevalence of stunting is the conventional anthropometric measure that reflects a long-term chronic undernutrition, failure of linear growth and multifactorial social deprivation. Unlike wasting, stunting is not affected by seasonality but rather related to the long-term effect of socio-economic development and long-standing food insecurity situation.
11
Stunting represent poor nutrition in the first 1,000 days of a child’s life. In these crucial days, the building
blocks are established for the development of the brain and for future growth. Any alteration in this stage has
long-term implications, and the damage caused by undernutrition in the early years of life is largely
irreversible and associated with impaired cognitive ability and reduced school and work performance.
TABLE 10: PREVALENCE OF STUNTING BASED ON HEIGHT FOR AGE
All
n = 707
Boys
n = 350
Girls
n = 357
Prevalence of stunting
(<-2 z-score)
(170) 24.0 %
(20.9 - 27.5 95% C.I.)
(99) 28.3 %
(23.7 - 33.4 95% C.I.)
(71) 19.9 %
(16.0 - 24.4 95%
C.I.)
Prevalence of moderate
stunting
(<-2 z-score and >=-3 z-
score)
(139) 19.7 %
(16.7 - 23.0 95% C.I.)
(77) 22.0 %
(17.8 - 26.8 95% C.I.)
(62) 17.4 %
(13.7 - 21.8 95%
C.I.)
Prevalence of severe
stunting
(<-3 z-score)
(31) 4.4 %
(3.1 - 6.2 95% C.I.)
(22) 6.3 %
(4.3 - 9.2 95% C.I.)
(9) 2.5 %
(1.3 - 5.0 95% C.I.)
Analysis of stunting prevalence based on height for age revealed an overall stunting rate of 24% (20.9-27%,
95% C.I.) and a severe stunting 4.4 % (3.1 - 6.2 95% C.I.).
When compared with the SMART survey conducted in 2017, the results shows that the stunting from this
survey is relatively lower than the 2017 survey which recorded a stunting of 26.1%.The decline in the stunting
rates can be attributed to the increase in number of nutrition interventions in the informal settlements.
3.2.5 Prevalence of Overweight.
Child growth is an internationally accepted outcome area reflecting child nutritional status. Child overweight
refers to a child who is too heavy for his or her height. This form of malnutrition results from expending too
few calories for the amount of food consumed and increases the risk of no communicable diseases later in
life. Child overweight is one of the World Health Assembly nutrition target indicators. Child growth is the most
widely used indicator of nutritional status in a community and is internationally recognized as an important
public-health indicator for monitoring health in populations. Prevalence of overweight (weight for height >+2
standard deviation from the median of the World Health Organization (WHO) Child Growth Standards) among
children under 5 years of age. In Nairobi County informal settlements, the prevalence was 2.6% (1.7-4.2)
with girls being more overweight than boys.
12
TABLE 11: PREVALENCE OF OVERWEIGHT
All
n = 717
Boys
n = 360
Girls
n = 357
Prevalence of
overweight (WHZ > 2)
(19) 2.6 %
(1.7 - 4.2 95% C.I.)
(8) 2.2 %
(1.1 - 4.6 95% C.I.)
(11) 3.1 %
(1.6 - 5.9 95% C.I.)
Prevalence of severe
overweight (WHZ > 3)
(0) 0.0 %
(0.0 - 0.0 95% C.I.)
(0) 0.0 %
(0.0 - 0.0 95% C.I.)
(0) 0.0 %
(0.0 - 0.0 95% C.I.)
3.3 ACCESS AND UTILIZATION OF HEALTH AND NUTRITION SERVICES
3.3.1 Vitamin A supplementation
Vitamin A deficiency is a major contributor to the mortality of children under five years of age. Therefore, improving the vitamin A status of children aged 6-59 months through supplementation enhances their resistance to disease and can reduce mortality from all causes by approximately 23 %4.Thus high supplementation coverage is critical by not only to eliminating vitamin A deficiency as a public-health problem but also as a central element of the child survival agenda. Additionally, this is an essential micronutrient for the immune system and that plays an important role in maintaining the epithelial tissues in the body. Severe Vitamin A Deficiency (VAD) can cause eye damage and increase severity of infections such as measles and diarrheal diseases in children in addition to slow recovery from illnesses. The survey results showed that the overall proportion of children (12-59 Months) supplemented with Vitamin twice in the period of one year preceding the survey was 46.4%. This is way below a national target of 80% with 80.5% reported to have received only once. However, 83.5 % children aged 6-11 months had received Vitamin A supplements once. Overall, 80.9% of children aged 6-59 months had received vitamin A at least once however this does not meet the required recommendation of twice yearly supplementation.
4 Beaton, George H., et al., ‘Effectiveness of Vitamin A Supplementation in the Control of Young Child
Morbidity and Mortality in Developing Countries’, ACC/SCN State-of-the-Art Series, Nutrition Policy Paper No. 13, Geneva, 1993.
13
FIGURE 5: VITAMIN A SUPPLEMENTATION (6-59 MONTHS)
3.3.2 Deworming
Periodic deworming for organisms like helminthes and schistosomiasis (bilharzia) can improve children’s
micronutrient status. On deworming coverage, the results showed only 69.5%. Children aged 12-59 months
were dewormed
3.3.2 Child Immunizations
According to the guidelines developed by the World Health Organization, children are considered to have received all basic vaccinations when they have received a vaccination against tuberculosis (also known as BCG), three doses each of the DPT-Hep B-Hib (also called pentavalent), polio vaccines and a vaccination against measles. The BCG vaccine is usually given at birth or at first clinical contact, while the DPT-Hep B-Hib and polio vaccines are given at approximately age 6, 10, and 14 weeks. Measles vaccinations should be given at or soon after age 9 months and 18 months. Information on immunization coverage was obtained in two ways: from written vaccination records, including the Mother and Child Health Booklet, other health cards and from mothers’ verbal reports. All mothers were asked to show the interviewer health cards used for the child’s immunization. From the survey results, 89.1% (n=659) of children were reported to have received BCG as confirmed by the Scar. Overall, In terms of Measles vaccination at 9 months, 97.2% of the children had received the vaccination
where 45.3% confirmed by card while 51.9% confirmed by recall. At 18 months, 84.4% had received measles
vaccination where 37.3% were confirmed by card while 47.1% was by mothers recall. In terms of OPV 1,
99.2% had received the immunization where 50.3% was confirmed by card while 48.9% was by recall. For
OPV 3, 96.8% had received the immunization where 49.1% was confirmed by card while 47.7% was
confirmed by recall. This is as shown in the graph below:
83.5%80.5%
46.4%
80.9%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
Vitamin ASupplimentation (6-11
Months )- Once
Vitamin ASupplementation (12-59
Months) - Once
Vitamin ASupplementation (12-59
Months) - Twice
Vitamin ASupplementation (6-59
Months) -once
Vitamin A Supplementation
14
FIGURE 6: MEASLES, OPV1 AND OPV3 COVERAGE
3.3.3 Morbidity Undernutrition and childhood morbidity have a synergistic relationship. The interrelationship of the two is in such a way that illness can suppress appetite precipitating undernutrition of a child while, on the other hand, nutritional deficiencies increase the susceptibility of the child to infectious diseases. Only 26.8% (212) of children aged 6-59 months in Nairobi County were reported to have been ill two weeks prior to survey with the most prevalent illness during this period was acute respiratory illnesses/ cough at 47.9%, fever with chills (26.0%) and watery diarrhea (17.0%) as shown in the graph below:
FIGURE 7: CHILD MORBIDITY
Further analysis on the children who had diarrhea showed that the prevalence of watery diarrhea was 20.1%
(n=58) and for bloody diarrhea at 0.0% (n=0). For the children with watery diarrhea only 60.3% were
supplemented using zinc which is below the national target of 80%.This is as highlighted in the table below:
Table 11: Diarrhoea cases
n N %
45.3%
37.3%
50.3%
49.1%
51.9%
47.1%
48.9%
47.7%
0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0%
Measles at 9 Months
Measles at 18 Months
OPV 1
OPV 3
Immunization Coverage
Yes by Card Yes by Recall
35.4%
65.1%
23.1%
35.8%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
Prevalence of Fever Prevalence of ARI Prevalence of WaterlyDiarrhoea
Prevalence of Others
Child Morbidity
15
Prevalence of Watery Diarrhea 49 212 20.1%
Zinc Supplementation/ORS 29 49 59.2%
3.3.4 Health Seeking Behaviour
Prompt and appropriate health seeking is critical in the management of childhood illnesses and prevention
of mortality. A number of factors have been identified as the leading causes of poor utilization of primary
health care services. These include but not limited to poor socio-economic status, lack of accessibility, cultural
beliefs and perceptions, low literacy level of the mothers and large family size.
Among the children who were reported sick in the past 2 Weeks, 72.2% were able to seek for medical
attention with majority seeking from private clinics and public clinics at 48.9% and 43.9% respectively.
Moreover others seek medical attention from the NGOs (2.2%) and from the community health volunteers
(1.3%). This is as shown in the graph below.
FIGURE 8: HEALTH SEEKING BEHAVIOUR
3.4 WATER AND SANITATION
3.4.1 Main source of water
The Kenya's 2010 Constitution acknowledges access to clean and safe water as a basic human right. It
assigns the responsibility for water supply and sanitation service provision to the County government. This
provides rights for citizens to access sufficient, safe, acceptable and affordable water for personal and
domestic uses. An adequate amount of safe water is necessary to prevent death from dehydration, to reduce
the risk of water-related diseases and for consumption, cooking, personal use and domestic hygienic
requirements.
Water and sanitation are deeply interrelated. Sanitation is essential for the conservation and sustainable use of water resources, while access to water is required for sanitation and hygiene practices. Furthermore, the realization of other human rights, such as the right to the highest attainable standard of health, the right to food, right to education and the right to adequate housing depends very substantially upon the implementation of the right to water and sanitation. Increasingly current evidence on poor WASH indicators
2.0%
49.0% 51.0%
1.3%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
Community Health worker Private Clinic/Pharmacy Public clinic NGO/FBO
Health seeking Behaviour
16
is being linked to under nutrition and more so on high stunting levels. Diarrheal, the leading killer of young children is closely linked to poor/inadequate5 WASH service. According to the survey, 89.5% of the households have piped water (yard, tap, dwelling), 6.0 % got water
from the water kiosk, 2% from borehole, 1%from Tanker and 0.4% from the Cart. This is shown in the
graph below:
FIGURE 9: MAIN WATER SOURCES
FIGURE 10: MAIN SOURCE OF WATER
3.4.2 Water Consumption
According to the Sphere standards for WASH, the average water use for drinking, cooking and personal
hygiene in any household should be at least 15 liters per person per day. Overall, 55.1% the household
consumed more than 15 liters per day with the mean water consumption per household being 63.6 liters. The
water rationing by the Nairobi Water Services was a major contributor to the low level of water consumption
in addition to the cost of buying water from vendors. Therefore many households in the informal settlements
could not afford. This is as highlighted in the table below:
TABLE 12:WATER CONSUMPTION
Water Quantity Consumption Nairobi Mean water consumption per HH
HH consuming <15litres per day 44.9%(448) 63.6 Liters
HH consuming >15litres per day 55.1%(549)
5 KDHS 2009
0.1%
0.1%
0.4%
0.8%
1.0%
2.0%
6.0%
12.4%
16.1%
30.2%
30.8%
0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0%
Protected well
Unprotected well
Cart with small tank
Others
Tanker truck
Tube well/Borehole
Water Kiosk
Piped to Neighbour
Piped into dwelling
Public tap/standpipe
Piped to yard/plot
Main Water Source
17
3.4.3 Access of Water
According to the minimum Sphere standards for WASH, the maximum distance from any household to the nearest water point should be 500 meters with the maximum queuing time at a water source for not more than 15 minutes .in addition should not take more than three minutes to fill a 20-litre container. The survey results showed that 97.9% (976) of the households had a trekking distance of less than 500m or less than 15 minutes to get water point while 2.1% trekked for 500m to 2km or 15 minutes to 1 hour to get water. In terms of queuing at water points, the majority 70.4%(421) indicated that the queued for less than 30 minutes while 18.1% queued for between 30 minutes to 1 hour. It worth noting 11.5% (69) of the household residence queued for more than 1 hour at the water point. This is as shown in the below table. TABLE 13: TREKKING AND QUEUEING FOR WATER
Indicator Category n %
Trekking distance to the Water Point
Less than 500m (<15min) 976 97.9%
>500m to <2km(15 to 1 hour) 3 0.3%
More than 2 km 18 1.8%
Queueing time at the water point
Less than 30 minutes 421 70.4%
30-1 hour 108 18.1%
More than 1 hour 69 11.5%
3.4.4 Access to Sanitation Facility
Appropriate sanitation practices are crucial in reducing food and waterborne diseases. Poor sanitation such
as open defecation has been linked to increase in chronic malnutrition in children.6 Hygienic sanitation
facilities are crucial for public health.Overally,99.9% of the households reported that they have access to
toilets where 22% reported to have access to pit latrine with slab, 46% had flush to piped sewer system,
6% had pit latrine without slab while 5% had flush to septic tank.
This is as summarized in the graphs below:
FIGURE 11: SANITATION FACILITY
6 9 UNICEF “Fast Facts And Figures About Hand washing”
0%
1%
2%
2%
5%
5%
6%
6%
7%
22%
46%
0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
Bucket
No facility /Bush/field
Flush to open drain
Flush to Pit latrine
Ventilated Improved Pit Latrine
Flush to septic tank
Pit latrine without slab/open pit
Flush to Don’t Know where
Other
Pit latrine with slab
Flush to piped sewer system
Sanitation Facility
18
3.4.5 Water Treatment and Hand washing
Handwashing with soap is one of the most effective and inexpensive interventions for preventing diarrheal diseases and pneumonia which account for 3.5 million child deaths annually worldwide. Overall, interventions to promote handwashing might save a million lives a year. Each person should be able to wash hands with water and soap after toilet use, before food preparation, before eating and after cleaning babies.
The results of the survey showed that only 47.0% (n=469) of the households reported treating water before drinking with majority of the respondent 64.8% (304) use boiling the water, 42.5 % (198) used chemicals while only 0.8% (4) used pot filters. Moreover, the results for handwashing at four critical times showed that among the caregivers interviewed only 12.5% (n=125) reported practicing proper hand washing at the 4 critical times.
TABLE 14: HANDWASHING AT CRITICAL TIMES AND WATER TREATMENT
Indicator n %
Water Treatment
Water Treatment 469 47.0%
Boiling 304 64.8%
Chemicals 198 42.2%
Pot filters 4 0.9%
Hygiene
Household Which wash Hands 946 94.9%
After Toilet 849 89.7%
Before cooking 418 44.2%
Before Eating 831 87.8%
After taking children to the toilet 158 34.1%
Hand washing by Soap and water 812 81.4%
hand washing 4 critical times 125 12.5%
3.4.6 Payment and Water Storage
To avoid physical contamination of water, households are encouraged to use close containers to store water.
With regard to water storage, over 90% of the resident in Nairobi County store water in closed container/Jerri
can. Significantly, overall, 65.7% (655) pay for water with 82.7% (542) paying per 20Litre Jerri can while
only17.3% (113) paying on monthly basis.
TABLE 15: WATER STORAGE AND PAYMENT
Indicator Category n %
Water Storage Open Container/Jerri can 96 9.6%
Closed Container/Jerri can 901 90.4%
Pay for Water Pay for Water 655 65.7%
Mode of Payment Per 20L Jerri can 542 82.7%
Per month 113 17.3%
19
3.5: Ownership of mosquito net Mosquito net are known to be highly effective in reducing malaria morbidity and mortality. However, usage
varies among households, and such variations in actual usage may seriously limit the potential impact of
nets. The survey sought to know on ownership and results showed that in terms of mosquito net ownership,
65.2% of the households had the mosquito net while only 33.8% did not have the mosquito nets. This is as
shown in the graph below:
FIGURE 12: MOSQUITO NET OWNERSHIP
3.6 MATERNAL NUTRITION
3.6.1: Maternal Nutrition Status
Maternal malnutrition is usually associated with high risk of low birth weights therefore, it is recommended that before, during and after birth, the maternal nutrition status should be optimal because it has direct impact on child survival. The maternal malnutrition was defined as women whose MUAC measurements were < 21.0cm while women whose MUAC measurements were between 21.0 <23.0cm were classified as at risk of malnutrition. The proportion of malnourished Women of Reproductive Age was at only 1.1% while 4.1% were at risk of malnutrition. Moreover only 0.6% of the pregnant and lactating women malnourished as shown in the table below. TABLE 16: MATERNAL NUTRITION MUAC
3.6.2 IFAS Supplementation
Iron deficiency is caused by inadequate iron intake to meet normal requirements or increased requirements due to excessive blood loss and reproduction. Among the mother with children less than 24 months, 88.4% (n=403) of had been supplemented with Iron Folic acid in their last pregnancy. However, the mean number of days IFAS was consumed by the women was on 9.9 days. In addition, 42.2% (n=170) of the women
65.2%
34.8%
0%
10%
20%
30%
40%
50%
60%
70%
Yes No
Mosquito Net Ownership
Indicator n N %
MUAC <21.0 cm for all women 10 920 1.1%
MUAC (210 - <230 mm) for all
WOMENwomen
38 920 4.1%
MUAC <21.0 cm for PLW 3 472 0.6%
20
consumed the IFAS less than 90 days while 53.8% consumed between 90 and 180 days while only 4.0% consumed for more than 180 days. This is as summarized in the graph below:
FIGURE 13: IFAS SUPPLEMENTATION
3.7 FOOD SECURITY
3.7.1 Minimum Dietary Diversity (24-Hour Recall)-Women Women of reproductive age (WRA)7 are often nutritionally vulnerable because of the physiological demands of pregnancy and lactation. Sub optimal nutrient intakes before and during pregnancy and lactation can affect both women and their infants. Yet in many resource poor environments, diet quality for WRA is very poor and there are gaps between intakes and requirements for a range of micronutrients8. In assessing the nutritional quality and quantity of the food consumed by the women of reproductive age, a 24 hour recall period household dietary diversity questionnaire was administered and consumption of 10 food groups. In terms of maternal nutrition practices, the survey results showed that majority of the women aged 15-49 years consumed starchy foods (97.0%), other vegetables (56.0%), vitamin A vegetables (77.6%), dairy products (38.0%) and other fruits (43.8%). This is as summarized in the graph below:
7 For the purposes of this document and indicator, WRA are defined as those 15–49 years of age. 8 Arimond et al., 2010; Lee et al. 2013
42.2%
53.8%
4.0%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
Below 90 Days 90≥180 Days Above 180 Days
IFAS Supplementation
21
FIGURE 14: WOMEN DIETARY DIVERSITY
3.7.2 Minimum Dietary Diversity for Women
MDD-W9 is a dichotomous indicator of whether or not women 15-49 years of age have consumed at least
five out of ten defined food groups the previous day or night. The proportion of women 15–49 years of age
who reach this minimum in a population can be used as a proxy indicator for higher micronutrient adequacy
and an important dimension of diet quality. This indicator constitutes an important step towards filling the
need for indicators for use in national and subnational assessments.
It is a population-level indicator based on a recall period of a single day and night so although data are
collected from individual women, the indicator cannot be used to describe diet quality for an individual woman.
This is because of normal day-to-day variability in individual intakes.
Only 59.6% met the minimum dietary diversity (MDDS).
FIGURE 15: MDD-W
9 Additional background on the indicator is available at: http://www.fantaproject.org/monitoring-and-evaluation/ minimum-dietary-diversity-
women-indicator-mddw.
97.0%
52.7%
11.8%
38.0%
35.7%
25.5%
77.6%
56.0%
88.9%
43.8%
0.0% 20.0% 40.0% 60.0% 80.0% 100.0% 120.0%
All starchy staple foods
Beans and peas
Nut and seeds
Dairy (Milk)
Flesh foods
Eggs
Vitamin A rich dark green leafty Vegetables
Other Vitamin A rich vegetables and fruits
Other Vegetables
Other fruits
40%
60%
MDD-W
< 5 Food groups 5 and more food groups
22
3.7.3 Household Dietary Diversity (24 hour Recall)
In assessing the nutritional quality and quantity of the food consumed by the survey population, a 24 hours retrospective household dietary diversity questionnaire was administered that helped to determine the households’ economic capacity to consume various foods in the County. At least >70% of the population within the last 24 hours at the time of the survey consumed five main food groups which include; Vegetables, cereals, Fruits, fats and oils and sweets. In addition, Fish, tubers and Condiments were consumed by at least <50% of the surveyed population. This is as shown in the graph below
FIGURE 16: HOUSEHOLD DIETARY DIVERSITY
3.7.4 Average days food groups are consumed showing consumption of micronutrients The poor quality of the habitual diet and the lack of dietary diversity in much of the developing world contribute to deficiencies of micronutrients. Micronutrient malnutrition is a global problem much bigger that imposes enormous costs on societies in terms of ill health, lives lost, reduced economic productivity and poor quality of life. Addressing the global challenge of micronutrient malnutrition requires the need for many strategies – both short- and intermediate-term and long-term sustainable approaches. In addition to the conventional approaches of micronutrient supplementation and fortification, promoting sustainable food based approaches to enable adequate intakes of micronutrients by much of the population includes dietary diversification strategies and agriculture-based approaches. Survey results on the average day’s food groups are consumed highlighting the consumption of micronutrients showed that fruits and vegetables were most consumed at an average of 6.7 days followed by oils and fats at 6.2 days and lastly, vitamin A were the least consumed at an average of 3.4 days. This is as highlighted in the graph below:
78.3%
15.6%
88.1%
41.6%
14.2%
11.4%
10.0%
24.9%
30.3%
85.4%
78.3%
76.2%
0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0%
Cereals and cereal products
White tubers and roots product
Vegetables
Fruits
Meat
Eggs
Fish
Pulses/legumes, nuts
Milk and milk products
Oils/fats
Sweets:
Condiments,
Food groups consumed by Household
23
FIGURE 17: AVERAGE NUMBER OF DAYS OF CONSUMPTION OF MICRONUTRIENT RICH FOODS
3.7.5 Food Consumption Score
The food consumption score is an acceptable proxy indicator to measure caloric intake and diet quality at the
household level by giving an indication of food security status of the household. It’s a composite score based
on dietary diversity, food frequency and relative nutritional importance of different food groups. The survey
results showed that majority of the households in Nairobi County (83.1%) had a good food consumption score
while 12.2% were at the border food consumption score with only 4.6% having poor food consumption score.
This is as shown in the graph below:
FIGURE 18: FOOD CONSUMPTION SCORE
3.8 Food Fortification
Fortification is adding vitamins and minerals to foods to prevent micronutrients deficiencies. The nutrients
are regularly used in grain fortification to prevent diseases, strengthen immune systems and to improve
productivity and cognitive development. Wheat flour, maize flour, and rice are primarily fortified to:
• Prevent nutritional anemia
6
5.4
6.7
5.3
3.4
6.2
0
1
2
3
4
5
6
7
STAPLES PROTEIN FRUITS &VEGES Iron Vitamin A Oils/Fats
4.6%12.2%
83.1%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
Poor Food Consumption Border Food Consumption Good Food Consumption
24
• Prevent birth defects of the brain and spine
• Increase productivity
• Improve economic progress
Only 25.5% (n=254) household reported to have heard about Food fortification with 40.6% having heard
through the health talk, 35.8% through the radio and 25.6 % through TV show. This is as shown in the
graphs below:
3.9 Coping Strategy Index
The Coping Strategy Index (CSI), a tool developed by the World Food Programme, is commonly used as a
proxy indicator for access to food10.It is a weighted score that allows one to measure the frequency and
severity of coping strategies. Data is collected on the number of days in the last seven days a household
used a specific coping strategy due to a shortage of food and/or income.
The mean coping strategy Index for Nairobi County was 6.53 this is as summarized in the table below:
TABLE 17: COPING STRATEGY INDEX
Percentage of HH(530) Frequency score (0-7)
Severity score (1-3)
Weighted score=Freq*weight
Rely less 1.4 1 1.4
Borrow Food 0.55 2 1.1
Limit Portion 0.95 1 0.95
10 Access to food’ is just one of the three pillars of food security. Other pillars include, ‘food availability’ and ‘food
utilization’.
35.8%
13.0%
4.3%
40.6%
25.6%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
45.0%
Where they Heard or learn about
Food Fortification
2.6%
85.9%
11.1%
Bought from a nearby
Posho mill
Bought from the shops
and supermarket
Maize is taken for milling
at a nearby posho mill
Main Source of Maize Flour Consumed
in the Household
FIGURE 19: FORTIFICATION AND MAIN MAIZE FLOUR CONSUMED
25
Restrict Consumption 0.68 3 2.04
Reduce Meals 1.04 1 1.04
6.53
4.0: Conclusions
The acute malnutrition situation in the Nairobi informal settlements is low according to the World Health Organization classification. However, in terms of caseloads due to high population density in the Nairobi County, the number remains considerably high. Despite reduction in the stunting and underweight level, the rate still remain high at 24% and 9.6% respectively. However, there was notable difference in underweight distribution among boys and girls with underweight rates 10.5% and 8.6% respectively. In terms of morbidity as a major contributor to malnutrition, the situation improved significantly compared to the previous year. The proportion of children reported ill 2 weeks before the study significantly dropped from 46.1% in 2017 to 38.9% in 2020 indicating a relatively more healthy population. Among the children reported ill, major ailments included ARIs at 53.5%, Fever at 29.5% and watery diarrhea at 20.1%.Significantly, poor water and sanitation hygiene conditions in informal settlements were major contributor to childhood illnesses mainly diarrhea, coupled with other poor hygiene practices. Only 12.5% people practice hand washing at 4 critical times. This depict a deterioration in appropriate hygiene practices hence contributing highly to high malnutrition rates in the county.
4.1: Recommendations
TABLE 18: RECOMMENDATIONS
Findings Recommendation Who is responsible Timelines
High Stunting Rates BFCI Intervention is
recommended. This
should be integrated
with implementation of
multisector
interventions with
emphasizes the
linkages with different
sectors to address both
immediate and
underlying causes of
malnutrition.
-Implement the multi
sectoral CNAP.
County Health Team
Management and the
Implementing Partners.
Continues
26
Low Knowledge on
MNPs
Health education and
sensitization on food
fortification should be
done to be done at both
community and health
facility level.
County Health Team
Management and the
Implementing Partners.
Continuous
Low GAM rate, however
in terms of caseloads
the numbers still remain
high
Procure RUSF for
management of
moderate acute
malnutrition
County Health Team
Management and the
Implementing Partners.
Continues
Low rate of IFAS
consumption
Provide health
education on
importance of IFAS.
Procure IFAS
County Health Team
Management and the
Implementing Partners.
Continues
Immediately
Poor hygiene Practices. Implement WASH
SBCC Strategy.
Use school health
platform to conduct
health education on
WASH
Train more Day care
providers/ ECD
teachers on WASH
Sensitize community on
WASH practices
Immediately
Low VAS twice yearly
supplementation
coverage
Use Day care/ECDE
centers to supplement
children
Sensitize health
workers on
documentation and
reporting of vitamin A
County Health Team
Management and the
Implementing Partners.
During Malezi Bora
PERIOD
27 | P a g e
APPENDICIES
APPENDIX 1: PLAUSIBILITY RESULTS
Indicator Acceptable
values/range
Nairobi County
Flagged data
(% of out of range subjects)
<7.5 0 (1.6 %)
Overall sex ratio (significant CHI square) >0.001 0 (p=0.853)
Age ratio (6-29vs 30-59) Significant CHI square >0.001 10 (p=0.000)
Dig. prevalence score-weight <20 0 (4)
Dig. prevalence score-height <20 0 (6)
Dig. prevalence score-MUAC <20 0 (7)
Standard Dev. Height WHZ >0.80 0 (1.07)
Skewness WHZ <±0.6 0 (0.00)
Kurtosis WHZ <±0.6 0 (-0.16)
Poisson WHZ -2 >0.001 0 (p=0.625)
OVERALL <24 10% (Good)
Page 28 of 58
APPENDIX 2: CALENDAR OF LOCAL EVENTS
2015 2016 2018 2019
Event Age Event Age Event Age Event Age
January Two buildings collapsed in Nairobi;
Happy New Year
48 New Year 36 Swearing in of
Raila;Prime Minister
of India visited
Kenya
24 New Year; Safaricom Jazz; Dusit
attack
12
February Valentines day; 47 Valentines; NYS
Scandal
35 Valentine’s Day;
Deportation of
Miguna
23 Valentine’s Day; Nurses Strike 11
March 46 34 Handshake; Heavy
Rains
22 Ethiopian air crash 10
April Garrisa University attack; Easter
Holidays; School Holidays
45 Easter Holiday; School
Holidays; ICC case
Withdrawn
33 Easter Holidays; 21 Easter Holiday; School holidays 9
May Labour Day; Malezi Bora 44 Labour day; Malezi
Bora; Collapse of
Huruma building
32 Royal Wedding;
Labour Day
20 Huduma number deadline; 8
June Madaraka Day; 43 Madaraka Day; 31 World Cup,
Madaraka Day; IDD
Holiday
19 Malikheight fire; New currency 7
July Obama's Visit; IDD Holiday 42 Deportation of Koffi
Olomide; IDD Holiday
30 Obamas Visit 18 Death of Bob collymore,Joyce Laboso
and Ken Okoth;
6
Page 29 of 58
August School Holidays; 41 School Holidays; 29 School Holidays 17 Census; Koen Killing; 5
September 40 28 Sharon Otieno
murdered; Jowie
and Maribe saga
16 Likoni Tragedy;Precious school
accident; Moneyheist
4
October Mashujaa Day; 39 Teargas Monday 27 Fort Tenan accident; 15 Eneos record 3
November Malezi Bora; National Exams;
School Holiday
38 Malezi bora; Trump
won the elections;
Release of KCPE
Results
26 Detention of
OBADO; Doctors
strike
14 Unveiling of BBI report 2
December Jamhuri Day; Death of the former
Mayor; Christmass;Boxing Day;
New year Eve
37 25 Christmass and
Jamhuri Day
13 Christmass and Boxing Day; King Kaka
new song; Sonko arrested
1
Page 30 of 58
APPENDIX 4: QUESTIONNAIRES
NAIROBI SLUMS INTEGRATED SMART HEALTH & NUTRITION SURVEY QUESTIONAIRE
1.IDENTIFICATION 1.1 Data Collector___________________ 1.2 Team Leader_______________ 1.3 Survey date
(dd/mm/yy)--------------------------
1.4 County 1.5 Sub
County
1.6 Ward 1.7
Location
1.8 Sub-
Location
1.9
Village
1.10 Cluster
No
1.11 HH
No
1.12 Team
No.
1.13
Household
geographical
coordinates
Latitude
_________
_
Longitude
___________
___
2. Household Demographics
2.1 2.2a 2.2b 2.3 2.4 2.5 2.6 2.7a 2.7b 2.8 2.10
Age Group
Please give
me the
names of
the persons
who usually
live in your
household.
Please
indicat
e the
house
hold
head
(write
HH on
the
memb
er’s
colum
n)
Age
(Record
age in
MONTHS
for
children
<5yrs and
YEARS
for those
≥
5 years’s)
Child
s age
verifie
d by
1=Hea
lth
card
2=Birt
h
certific
ate/
notific
ation
3=Bap
tism
card
4=Rec
all
5.
other
_____
___
specif
y
Sex 1= Male 2=
Fema
le
If between 3 and 18
years old, Is the child attending school?
1 = Yes 2 = No
(If yes go to
2.8; If no go
t o 2.7)
Main reason for not attending school (Enter one code from list) 1=Chronic Sickness 2=Weather (rain, floods, storms) 3=Family labour responsibilities 4=Working outside home 5=Teacher absenteeism/lack of teachers 6= Fees or costs 7=Household doesn’t see value of schooling 8 =No food in the schools
2.7a, What is the child doing when not in school? 1=Working on family farm 2=Herding Livestock 3=Working for payment away from home 4=Left home for elsewhere 5=Child living on the street 6: Other specify __________
What is the highest level of education attained?(level completed) From 5 yrs and above 1 =Pre primary 2= Primary 3=Secondary 4=Tertia
ry
5= None 6=others(specify) Go to
question
to 2.9 ↓
If the
househo
ld owns
mosquit
o net/s,
who
slept
under
the
mosquit
o net last
night?
(Probe-
enter all
response
s
mentione
d (Use 1 if
“Yes” 2 if
“No and 3
if not
applicabl
e) go to
question
2.11
Ye
ars
Mon
ths
Page 31 of 58
9 = Migrated/ moved from school area (including displacements) 10=Insecurity/violence 11-No school Near by 12=Married 13. Pregnant/ taking care of her own child 13=other
s
(specify)
…………
………..
< 5
YRS
1
2
3
4
>5 TO
<18
YRS
5
6
7
8
9
10
11
Page 32 of 58
12
ADULT
(18
years
and
above)
13
14)
15
16
2.9 How many mosquito nets does this household have? ____________________ (Indicate no.) go to question
2.10 before proceeding to question 2.11
2.1
1
Main Occupation of the Household Head – HH.
(enter code from list) 1=Livestock herding 2=Own farm labour 3=Employed (salaried) 4=Waged labour (Casual) 5=Petty trade 6=Merchant/trader 7=Firewood/charcoal 8=Fishing 9= Income earned by children 10=Others (Specify) |____|
2.12. What is the main current source of income of the household? 1. =No income 2. = Sale of livestock 3. = Sale of livestock products 4. = Sale of crops 5. = Petty trading e.g. sale of firewood 6. =Casual labor 7. =Permanent job 8. = Sale of personal assets 9. = Remittance 10. Other-Specify |____|
2.1
3
Marital status of the respondent
1. = Married 2. = Single 3. = Widowed 4. = separated 5. = Divorced. |____|
2.14. What is the residency status of the household?
1. IDP
2.Refugee
3. Resident |____|
2.1
5
Are there children who have come to live with you
recently?
1. YES 2. NO
2.15b If yes, why did the child/children come to live with you?
1= Did not have access to food
2=Father and Mother left home
3=Child was living on the street,
4=Care giver died
Page 33 of 58
5= Other specify
________________________________________________
Page 34 of 58
Fever with Malaria: High temperature with shivering
Cough/ARI: Any episode with severe, persistent cough or difficulty breathing
Watery diarrhoea: Any episode of three or more watery stools per day
Bloody diarrhoea: Any episode of three or more stools with blood per day
3. 4. 5. CHILD HEALTH AND NUTRITION (ONLY FOR CHILDREN 6-59 MONTHS OF AGE; IF N/A SKIP TO SECTION 3.6)
Instructions: The caregiver of the child should be the main respondent for this section 3.1 CHILD ANTHROPOMETRY 3.2 and 3.3 CHILD MORBIDITY
(Please fill in ALL REQUIRED details below. Maintain the same child number as part 2)
A
Chil
d
No.
B C D E F G H I J K 3.2 a 3.2 b 3.3 a 3.3 b 3.3 c
what is
the
relationsh
ip of the
responde
nt with
the
child/chil
dren
1=Mother
2=Father
3=Sibling
SEX
Female
…...F
Male
…..….
M
Exact
Birth
Date
Age in
month
s
Weigh
t
(KG)
XX.X
Heig
ht
(CM)
XX.X
Oedem
a
Y= Yes
N= No
MUAC
(cm)
XX.X
Is the child in any nutrition program 1. Ye
s 2. No If no skip to questions 3.2
If yes to question J. which nutrition program? 1.OTP 2.SFP 3.BSFP Other Specify
Has your child (NAME) been ill in the past two weeks? 1.Yes
2. No If No, skip to 3.4
If YES, which illness (multiple responses possible) 1 = Fever with chills like malaria 2 = ARI /Cough 3 = Watery diarrhoea 4 = Bloody diarrhoea 5 = Other (specify)
When the
child was sick
did you seek
assistance?
1.Yes 2. No
If the
response is
yes to
question # 3.2
where did you
seek
assistance?
(More than
one response
possible-
1. Traditional
healer
If the child had watery diarrhoea in the last TWO (2) WEEKS, did the child get: 1. ORS 2. Zinc
supplementation?
Show sample and probe further for this component check the remaining
Page 35 of 58
3.4 Maintain the same child number as part 2 and 3.1 above
A1 A2 B C D E F G H I
4=Grandm
other
5=Other
(specify)
______
See case definitions above
2.Community
health worker
3. Private
clinic/
pharmacy
4. Shop/kiosk 5.Public clinic
6. Mobile clinic
7. Relative or
friend
8. Local herbs
9.NGO/FBO
drugs(confirm from mother child booklet)
01
02
03
04
Page 36 of 58
Child No.
How
many
times has
child
received
Vitamin A
in the
past
year?
(show
sample)
Has the
child
received
vitamin A
suppleme
nt in the
past 6
months?
How many
times did
the child
receive
vitamin A
capsules
from the
facility or
out reach
If Vitamin
A
received
how
many
times in
the past
one year
did the
child
receive
verified
by
Card?
FOR
CHILDRE
N 12-59
MONTHS
How
many
times has
child
received
drugs for
worms
in the
past
year?
(show Sample)
Has the child received BCG vaccination? Check for BCG scar. 1 = scar 2=No scar
Has child received OPV1 vaccination 1=Yes, Card 2=Yes, Recall 3 = No 4 = Do not know
Has child received OPV3 vaccination? 1=Yes, Card 2=Yes, Recall 3 = No 4 = Do not know
Has child received measles vaccination at 9 months (On the upper right shoulder)? 1=Yes, Card 2=Yes, Recall 3 = No 4 = Do not know
Has child received the second measles vaccination (18 to 59 months ) (On the upper right shoulder)? 1=Yes, Card 2=Yes, Recall 3 = No 4 = Do not know
01
02
03
04
Page 37 of 58
3.5 MNP Programme Coverage.
Maintain the same child number as part 2 and 3.1 above. Ask all the relevant questions (3.5.1 to 3.6.4) before moving on to fill responses for the next
child. THIS SECTION SHOULD ONLY BE ADMINISTERED IF MNP PROGRAM IS BEING IMPLEMENTED OR HAS BEEN IMPLEMENTED
3.5 Enrolment in an MNP program 3.6 Consumption of MNPs
3.5.1.
Is the child enrolled in
the MNP program?(show
the example of the MNP
sachet)
(record the code in the
respective child’s
number)
3.5.2
If the child, 6-23months, is not
enrolled for MNP, give reason.
(Multiple answers possible.
Record the code/codes in the
respective child’s number.
DO NOT READ the answers)
3.6.1
Has the
child
consumed
MNPs in the
last 7
days?(show
s the MNP
sachet)
(record the
3.6.2
If yes, how frequent do
you give MNP to your
child? (record the code
in the respective
child’s number)
Every day ……..........……….1
3.6.3
If no, since when did
you stop feeding
MNPs to your child?
(record the code in
the respective
child’s number)
3.6.4
What are the reasons to
stop feeding your child with
MNPs? (Multiple answers
possible. Record the
code/codes in the
respective child’s
number. DO NOT READ
the answers)
Page 38 of 58
Yes =1
No=0
If no go to 3.5.2,
If yes go to section
3.6.1
Do not know about MNPs
….......………1
Discouraged from what I heard
from others
……...........................................
...2
The child has not fallen ill, so
have not gone to the health
facility …. ….....…..3
Health facility or outreach is far
….....…4
Ch ild receiving therapeutic or
supplementary foods
..............................5
Other reason, specify
...…….....……….6
Skip to 3.7
code in the
respective
child’s
number)
YES = 1
N0= 0
If no skip to
3.6.3
Every other day ........….……..2 Every third day ……......……..3 2 days per week at any day ....4 Any day when I remember..…5
1 week to 2 weeks
ago ....1
2 week to 1 month
ago ....2
More than 1 month
..........3
Finished all of the sachets
.............1
Child did not like it
.......................2
Husband did not agree to
give to the child
..................3
Sachet got damaged
………….4
Child had diarrhea after
being given vitamin and
mineral powder ……..5
Child fell
sick.......................6
Forgot
…………………….…..7
Child enrolled in IMAM
program …8
Other
(Specify)______________
..9
Page 39 of 58
Child
1
Child
2
Child
3
Child
4
Page 40 of 58
MATERNAL NUTRITION FOR WOMEN OF REPRODUCTIVE AGE (15-49 YEARS)(Please insert appropriate number in the box)
3.7 3.8 3.9 3.10 3.11
Woman ID. (all women in the HH aged 15-49 years from the household demographics – section 2 )
What is the mother’s /
caretaker’s
physiological status
1. Pregnant 2. Lactating 3. not pregnant and
not lactating 4. Pregnant and
lactating
Mother/
caretaker’s
MUAC reading:
____.__cm
During the pregnancy of
the (name of the
youngest biological child
below 24 months) did
you take the following
supplements? indicate
1. Yes 2. No 3. Don’t know 4. N/A
If Yes, for how many
days did you take?
(probe and
approximate the
number of days)
Iron
table
ts
syru
p
Folic
acid
Combin
ed iron
and folic
acid
supplem
ents
Iron
tablet
s
syrup
Foli
c
aci
d
Combi
ned
iron
and
folic
acid
supple
ments
Page 41 of 58
4.0 WATER, SANITATION AND HYGIENE (WASH)/- Please ask the respondent and indicate the appropriate number in the space provided
4.1 What is the MAIN source of drinking water for
the household NOW?
piped water
piped into dwelling ...................................... 11
piped to yard / plot ...................................... 12
piped to neighbour ...................................... 13
public tap / standpipe .................................. 14
tube well / borehole ....................................... 21
dug well
protected well .............................................. 31
unprotected well .......................................... 32
spring
protected spring .......................................... 41
unprotected spring ...................................... 42
rainwater ........................................................ 51
tanker-truck ................................................... 61
cart with small tank ....................................... 71
water kiosk .................................................... 72
surface water (river, dam, lake, pond, stream,
canal, irrigation channel) ............................. 81
packaged water
bottled water ............................................... 91
sachet water ............................................... 92
1.
4.2 a What is the trekking distance to the
current main water source?
1=less than 500m (Less than 15 minutes) 2=more than 500m to less than 2km (15 to 1 hour) 3=more than 2 km (1 – 2 hrs)
4=Other(specify) |____|
4.2b –
Who
MAINLY
goes to
fetch
water at
your
current
main
water
source?
1=Women
, 2=Men,
3=Girls,
4=Boys
4.2.2a
How long do you queue for water?
1. Less than 30 minutes 2. 30-60 minutes 3. More than 1 hour 4. Don’t que for water 1.
.3 Do you do anything to your water before
drinking? (MULTIPLE RESPONSES POSSIBLE)
(Use 1 if YES and 2 if NO).
1. Nothing 2. Boiling…………
……………………………………. |____| 3. Chemicals
(Chlorine,Pur,Waterguard)…………… |____|
|____|
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4. Traditional herb……………………………………... |____|
5. Pot filters…………………………………………….. |____|
5.
4.3a
|____|
6.
4.4 Where do you store water for drinking?
1. Open container / Jerrican 2. Closed container / Jerrican |____|
4.5 How much water did your household use
YESTERDAY (excluding for animals)?
(Ask the question in the number of 20 liter Jerrican and
convert to liters & write down the total quantity used in liters)
|____|
4.6 Do you pay for water?
1. Yes 2. No (If No skip to Question
4.7.1) |____|
4.6.1 If yes, how much per 20
liters jerrican _________
KSh/20ltrs
4.6.2 If paid per
month how much
|____|
4.7.1a
We would like to learn about where members of
this household wash their hands.
Can you please show me where members of your
household most often wash their hands?
Record result and observation.
OBSERVED
FIXED FACILITY OBSERVED (SINK / TAP)
IN DWELLING ................................................. 1
IN YARD /PLOT ............................................... 2
MOBILE OBJECT OBSERVED
(BUCKET / JUG / KETTLE) ...................... 3
NOT OBSERVED
NO HANDWASHING PLACE IN DWELLING /
YARD / PLOT ........................................... 4
NO PERMISSION TO SEE ................................ 5
4.7.1b Is soap or detergent or ash/mud/sand
present at the place for handwashing?
YES, PRESENT .......................................... 1
NO, NOT PRESENT .............. ……………………2
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4.7.1 Yesterday (within last 24 hours) at what instances did you wash your hands? (MULTIPLE
RESPONSE- (Use 1 if “Yes” and 2 if “No”)
1. After toilet………………………………………………………………………………………………………………
2. Before cooking………………………………………………………………………………………………………...
3. Before eating………………………………………………………………………………………………………….
4. After taking children to the toilet…………………………………………………………………………………….
5. Others………………………………………………………………………………………………………………….
|____|
|____|
|____|
|____|
|____|
4.7.2 If the caregiver washes her hands, then probe further; what did you use to wash your hands?
1. Only water 2. Soap and water 3. Soap when I can afford it 4. traditional herb 5. Any other specify |____|
4.8 What kind of toilet facility do members of
your household usually use?
If ‘Flush’ or ‘Pour flush’, probe:
Where does it flush to?
If not possible to determine, ask
permission to observe the facility.
flush / pour flush
flush to piped sewer system 11
|____|
Page 44 of 58
flush to septic tank 12
flush to pit latrine 13
flush to open drain 14
flush to DK where 18
pit latrine
ventilated improved pit
latrine 21
pit latrine with slab 22
pit latrine without slab /
open pit 23
composting toilet 31
bucket 41
hanging toilet /
hanging latrine 51
no facility / bush / field 95
1. OTHER (specify) 96
Page 45 of 58
5.0: Food frequency and Household Dietary Diversity
*Type of food* Did members of
your household
consume any food
from these food
groups in the last 7
days?(food must
have been
cooked/served at the
household)
0-No
1-Yes
If yes, mark days the food was consumed in the last 7
days?
0-No
1-Yes
What was the
main source of the
dominant food
item consumed in
the HHD?
1.Own
production
2.Purchase
3.Gifts from
friends/families
4.Food aid
5.Traded or
Bartered
6.Borrowed
7.Gathering/wild
fruits
8.Other (specify)
WOMEN DIETARY DIVERSITY
ONLY FOR WOMEN AGE 15 TO
49 YEARS. REFER TO THE
HOUSEHOLD DEMOGRAPHICS
SECTION Q2.3 AND Q2.5
Please describe the foods that
you ate or drank yesterday
during day and night at home or
outside the home (start with the
first food or drink of the morning)
0-No
1-Yes
D1 D2 D 3 D 4 D5 D 6 D7 TOTA
L
Woma
n
ID……
…
Woma
n
ID…
…..
Woma
n ID
…….
Woma
n
ID…
…..
5.1. Cereals and cereal
products (e.g. sorghum,
Page 46 of 58
maize, spaghetti, pasta,
anjera, bread)?
5.2. Vitamin A rich vegetables and tubers: Pumpkins, carrots, orange sweet potatoes
5.3. White tubers and roots: White potatoes, white yams, cassava, or foods made from roots
5.4 Dark green leafy vegetables: Dark green leafy vegetables, including wild ones + locally available vitamin A rich leaves such as cassava leaves etc.
5.5 Other vegetables (e.g., tomatoes, egg plant, onions)?
5.6. Vitamin A rich fruits: + other locally available vitamin A rich fruits
5.7 Other fruits
5.8 Organ meat (iron rich): Liver, kidney, heart or other organ meats or blood based foods
5.9. Flesh meats and offals: Meat, poultry, offal (e.g.
Page 47 of 58
goat/camel meat, beef; chicken/poultry)?
5.10 Eggs?
5.11 Fish: Fresh or dries fish or shellfish
5.12 Pulses/legumes, nuts (e.g. beans, lentils, green grams, cowpeas)?
5.13 Milk and milk products (e.g. goat/camel/ fermented milk, milk powder)?
5.14 Oils/fats (e.g. cooking fat or oil, butter, ghee, margarine)?
5.15 Sweets: Sugar, honey, sweetened soda or sugary foods such as chocolates, sweets or candies
5.16 Condiments, spices and beverages:
Page 1 of 58
4.1 FOOD FORTIFICATION (FF)/- Please ask the respondent and indicate the appropriate number in the space provided
1.1
1.1.1
Have you heard about food fortification?
1. Yes 2. No 3. Don’t know
If yes, where did you hear or learn about it? (MULTIPLE RESPONSE ARE POSSIBLE- (Use 1 if
“Yes” and 2 if “No”)
6. Radio………………………………………………………………………………………………………………
7. Road show………………………………………………………………………………………………………...
8. In a training session attended…………………………………………………………………………………….
9. On a TV show……………………………………………………………………………………. 10. Others……………………………………………………………………………………………………
…………….
|____|
|____|
|____|
|____|
|____|
1.2 Respondent’s knowledge on the food fortification logo
(Show the food fortification logo to the respondent and
record the response). Do you know about this sign?
1. Yes 2. No 3. Don’t know
|____|
1.3 What is the MAIN source of Maize flour for the
household NOW?
2. Bought from the shops, supermarket e.t.c 3. Maize is taken for milling at a nearby Posho Mill 4. Bought from a nearby Posho Mill 5. Other (Please specify)
|______________________________|
1.1b Do you know if the maize flour you
consume is fortified or not?
1. Yes 2. No 3. Don’t know
1.4 What brands of the following foods does your
household consume?
1. Maize flour 2. Wheat flour 3. Margarine 4. Oils 5. Fats 6. Sugar
|________________________________
|
Page 2 of 58
|________________________________
|
|________________________________
|
|________________________________
|
|________________________________
|
|________________________________
|
6. COPING STRATEGIES INDEX
Frequency score: Number of days out of the past seven (0 -7).
In the past 7 DAYS, have there been times when you did not have enough food or money to buy food?
If No; END THE INTERVIEW AND THANK THE RESPONDENT
If YES, how often has your household had to: (INDICATE THE SCORE IN THE SPACE PROVIDED)
1 Rely on less preferred and less expensive foods?
2 Borrow food, or rely on help from a friend or relative?
3 Limit portion size at mealtimes?
4 Restrict consumption by adults in order for small children to eat?
5 Reduce number of meals eaten in a day?
TOTAL HOUSEHOLD SCORE:
END THE INTERVIEW AND THANK THE RESPONDENT
Page 3 of 58